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Transient Analysis of a Selective Partial-Update LMS Algorithm
Full text linkIn applications where large-order filters are needed, the computational load of adaptive filtering algorithms can become prohibitively expensive. In this paper, a comprehensive analysis of a selective partial-update least mean squares, named SPU-LMS-M-min, is developed. By employing the partial-update strategy for a non-normalized adaptive scheme, the designer can choose an appropriate number of update blocks considering a trade-off between convergence rate and computational complexity, which can result in a more than 40% reduction in the number of multiplications in some configurations compared to the traditional LMS algorithm. Based on the principle of minimum distortion, a selection criterion is proposed that is based on the input signal’s blocks with the lowest energy, whereas typical Selective Partial Update (SPU) algorithms use a selection criterion based on blocks with highest energy. Stochastic models are developed for the mean weights and mean and mean squared behaviour of the proposed algorithm, which are further extended to accommodate scenarios involving time-varying dynamics and suboptimal filter lengths. Simulation results show that the theoretical predictions are in good agreement with the experimental outcomes. Furthermore, it is demonstrated that the proposed selection criterion can be easily extended to active noise cancellation algorithms as well as algorithms utilizing variable filter length. This allows for the reduction of computational costs for these algorithms without compromising their asymptotic performance.publishedVersio
Feature extraction and pattern recognition in time-lapse pressure transient responses
Full text linkMonitoring of modern wells equipped with permanent downhole gauges and flowmeters provides large datasets of pressure, temperature and flowrate measurements. On a limited scale, selected events from these datasets are traditionally used in well performance analysis and monitoring, reservoir simulation, and many other tasks employing physics-based models. New methods that combine model- and data-driven approaches for full-scale analysis of these large datasets have recently attracted interest, suggesting new metrics for knowledge extraction. Most recent studies have used a combination of Pressure Transient Analysis (PTA), which is a key reservoir engineering tool, with hybrid methods, such as PTA-metrics and AI-powered models. The emergence of hybrid methodologies combining model- and data-driven approaches has opened new perspectives for comprehensive analysis and knowledge extraction from big well monitoring data sets, accumulated in the industry. Despite their potential, these methodologies often face challenges in reliability, effective data processing, interpretation and feature engineering. This paper introduces a novel PTA-feature extraction and pattern recognition methods for analysis of time-lapse pressure transient responses and their Bourdet derivatives. The pattern recognition method builds on an unsupervised classification method to extract PTA-features, associated with different flow regimes commonly used in PTA. Each pressure transient in a time-lapse series is first processed by an autonomously fine-tuned algorithm that measures the signal's distance to an ensemble of physically meaningful responses defined by PTA-feature library, thus breaking the transient into a series of likely PTA-features. A set of hyperparameters is used in the unsupervised classification, where an optimization procedure is employed for automated tuning of the hyperparameters to a particular transient. Subsequently, recognition of underlying patterns governed by sequences of these PTA-features in the time-lapse transient responses is performed. Testing of the combination of these new methods through synthetic and field cases is further carried out with verification via comparison with expert’ interpretation results. Added value to the previously introduced PTA metrics, which provide on-the-fly well and reservoir performance analysis, is finally demonstrated. The proposed pattern recognition method improves reliability and automates the calculation of the PTA metrics. The developed methodology serves as a new tool for knowledge extraction from big well monitoring datasets, available in the companies operating in the oil and gas industry, as well as the emerging industries such as carbon capture and storage and geothermal energy production. The article concludes with a discussion of the main advantages and limitations of the suggested feature extraction and pattern recognition methods. Besides the combined use of the methods described in this article, these methods may also be integrated with conventional physics-based approaches widely used in the industry for well data interpretation and reservoir simulations, improving their performance and efficiency for big data sets.Feature extraction and pattern recognition in time-lapse pressure transient responsespublishedVersio
On the emission-path dependency of the efficiency of ocean alkalinity enhancement
Full text linkOcean alkalinity enhancement (OAE) deliberately modifies the chemistry of the surface ocean to enhance the uptake of atmospheric CO2. The chemical efficiency of OAE (the amount of CO2 sequestered per unit of alkalinity added) depends, among other factors, on the background state of the surface ocean, which will significantly change until the end of this century and beyond. Here, we investigate the consequences of such changes for the long-term efficiency of OAE. We show, using idealized and scenario simulations with an Earth system model, that under doubling (quadrupling) of pre-industrial atmospheric CO2 concentrations, the simulated mean efficiency of OAE increases by about 18% (29%) from 0.76 to 0.90 (0.98). We find that only half of this effect can be explained by changes in the sensitivity of CO2 sequestration to alkalinity addition itself. The remainder is due to the larger portion of anthropogenic emissions taken up by a high-alkalinity ocean. Importantly, both effects are reversed if atmospheric CO2 concentrations were to decline due to large-scale deployment of land-based (or alternative ocean-based) carbon dioxide removal (CDR) methods. By considering an overshoot pathway that relies on large amounts of land-based CDR, we demonstrate that OAE efficiency indeed shows a strong decline after atmospheric CO2 concentrations have peaked. Our results suggest that the assumption of a constant, present-day chemical efficiency of OAE in integrated assessment modeling and carbon credit assignments could lead to economically inefficient OAE implementation pathways.publishedVersio
Behovet for interkommunalt samarbeid i Norge – en kunnskapsoppsummering
Full text linkI dette prosjektet har vi studert nyere utredninger for å kartlegge dagens behov for interkommunalt samarbeid. Utredninger peker på at det finnes økt behov for interkommunalt samarbeid innen områdene samfunnsplanlegging, beredskap – brann og redning, digitalisering, IKT, rus og psykiatri. Det pekes videre på at kommunene i større grad burde samle dagens og fremtidens interkommunale samarbeid i flerfunksjonelle samarbeid med faste medlemskommuner. En del av argumentasjonen for opprettelse av mer helhetlig samarbeid ligger i behovet for å skape mer oversikt og bruke mindre ressurser på å koordinere "lappetepper" av samarbeid. Rapporten peker imidlertid på at det kan være utfordrende å finne én størrelse på interkommunalt samarbeid som er optimal for alle typer oppgaver. Noen oppgaver vil av geografiske hensyn heller ikke være av relevans for alle kommuner. Hva som anbefales som kriteriene for valg av samarbeidspartnere varierer også mellom sektorer.Behovet for interkommunalt samarbeid i Norge – en kunnskapsoppsummeringpublishedVersio
The first ensemble of kilometer-scale simulations of a hydrological year over the third pole
Full text linkAn accurate understanding of the current and future water cycle over the Third Pole is of great societal importance, given the role this region plays as a water tower for densely populated areas downstream. An emerging and promising approach for skillful climate assessments over regions of complex terrain is kilometer-scale climate modeling. As a foundational step towards such simulations over the Third Pole, we present a multi-model and multi-physics ensemble of kilometer-scale regional simulations for the hydrological year of October 2019 to September 2020. The ensemble consists of 13 simulations performed by an international consortium of 10 research groups, configured with a horizontal grid spacing ranging from 2.2 to 4 km covering all of the Third Pole region. These simulations are driven by ERA5 and are part of a Coordinated Regional Climate Downscaling EXperiment Flagship Pilot Study on Convection-Permitting Third Pole. The simulations are compared against available gridded and in-situ observations and remote-sensing data, to assess the performance and spread of the model ensemble compared to the driving reanalysis during the cold and warm seasons. Although ensemble evaluation is hindered by large differences between the gridded precipitation datasets used as a reference over this region, we show that the ensemble improves on many warm-season precipitation metrics compared with ERA5, including most wet-day and hour statistics, and also adds value in the representation of wet spells in both seasons. As such, the ensemble will provide an invaluable resource for future improvements in the process understanding of the hydroclimate of this remote but important region.publishedVersio
Likestillingsmonitor Agder for perioden 2017–2021
Full text linkDette er den tredje likestillingsmonitoren som lages for Agder basert på Statistisk sentralbyrås (SSBs) likestillingsindikatorer. Den første kom i 2011 og den forrige kom i 2015 og var utarbeidet av Agderforskning. Siden den gang er mange år gått, vi har hatt kommunesammenslåinger i Agder og vi er blitt ett Agder fra 2020. Denne rapporten har Senter for likestilling ved UiA og NORCE Norwegian Research Center i samarbeid planlagt, men det er NORCE som har ført i pennen denne oppdaterte monitoren med data for perioden 2017-2021. I tillegg blir tre dybdestudier utarbeidet i denne forbindelse og i denne andre versjonen av likestillingsmonitoren har vi tatt med et dybdestudie av kvinner i ledelse og uttak av deltid blant kvinner i Agder.Likestillingsmonitor Agder for perioden 2017–2021publishedVersio
Migratory contingents of brown trout reveal variable exposure to anthropogenic threats along a fjord-river continuum
Full text linkBrown trout is a partially migratory salmonid that makes use of diverse habitats to maximise growth and fitness. One of the most substantial threats to brown trout is infection with pathogens from open net-pen fish farming, which creates hotspots for pathogen reproduction and transmission. Western Norway is a global hotspot for both fish farming and wild salmonids, which generates conflicts due to the impacts of the farms on the behaviour, survival, and fitness of salmonids that overlap with farming activities. In this study, we tagged adult brown trout (>35 cm) at two spatiotemporal intervals that corresponded to two different life history stages: springtime in the river when trout were completing overwintering and summer in the fjord when trout were in their marine feeding phase. The tagging revealed three different behaviours, fish that remained in freshwater, fish that migrated between freshwater and the fjord, and fish that remained in the estuary. Although some trout moved >100 km to the outer fjord areas, most trout remained relatively close to the river. Depth sensor transmitters in a subset of trout also revealed that the trout remained in the upper water column. Most of the horizontal and vertical movements therefore resulted in spatial overlap with fish farming for the migratory trout, but not for resident trout that remained in the estuary or in freshwater. Findings reveal the challenges of managing a fish with such behavioural plasticity but the urgency of recognising how important inner fjord habitats are for migratory brown trout.publishedVersio
Microbial induced wettability alteration with implications for Underground Hydrogen Storage
Full text linkCharacterization of the microbial activity impacts on transport and storage of hydrogen is a crucial aspect of successful Underground Hydrogen Storage (UHS). Microbes can use hydrogen for their metabolism, which can then lead to formation of biofilms. Biofilms can potentially alter the wettability of the system and, consequently, impact the flow dynamics and trapping mechanisms in the reservoir. In this study, we investigate the impact of microbial activity on wettability of the hydrogen/brine/rock system, using the captive-bubble cell experimental approach. Apparent contact angles are measured for bubbles of pure hydrogen in contact with a solid surface inside a cell filled with living brine which contains sulphate reducing microbes. To investigate the impact of surface roughness, two different solid samples are used: a “rough” Bentheimer Sandstone sample and a “smooth” pure Quartz sample. It is found that, in systems where buoyancy and interfacial forces are the main acting forces, the impact of biofilm formation on the apparent contact angle highly depends on the surface roughness. For the “rough” Bentheimer sandstone, the apparent contact angle was unchanged by biofilm formation, while for the smooth pure Quartz sample the apparent contact angle decreased significantly, making the system more water-wet. This decrease in apparent contact angle is in contrast with an earlier study present in the literature where a significant increase in contact angle due to microbial activity was reported. The wettability of the biofilm is mainly determined by the consistency of the Extracellular Polymeric Substances (EPS) which depends on the growth conditions in the system. Therefore, to determine the impact of microbial activity on the wettability during UHS will require accurate replication of the reservoir conditions including surface roughness, chemical composition of the brine, the microbial community, as well as temperature, pressure and pH-value conditions.publishedVersio
Grunnlag for valg av ryddestrategi
Full text linkSom del av prosjektet Rydderisk - Beslutningsmatrise for effektiv og skånsom rydding av ulike miljøer, har vi undersøkt mulige negative miljøvirkninger av rydding av plast. En konseptuell beslutningsmatrise er etablert som gir anbefalinger om rydding kan gjennomføres, vurderes, eller ikke anbefales basert på grad av rydderelatert risiko knyttet til miljøsårbarhet og avfallets type, tilstand og interaksjon med naturen. Kompleksiteten av mulige eventualiteter som kan oppstå i miljøet krever en vekting av de faktorer som bidrar til avfallsrelatert rydderisiko. Vekting av relevante faktorer kan være basert på visuelle observasjoner i felt eller bildedata fra droner som så registreres i en vektingsmatrise. Grunnlaget for vurdering av miljøsårbarhet er sammenstilt med utgangspunkt i litteraturstudier, intervjuer med fageksperter og gjennomgang av relevant lovverk. Samlet sett bidrar denne sammenstilling, strukturering og vekting basert på eksisterende kunnskap grunnlaget for videre utvikling av et digitalt beslutningsverktøy for sikker plastrydding.Grunnlag for valg av ryddestrategipublishedVersio
CO2 and hydrography acquired by autonomous surface vehicles from the Atlantic Ocean to the Mediterranean Sea: data correction and validation
Full text linkThe ATL2MED demonstration experiment involved two autonomous surface vehicles from Saildrone Inc. (SD) which travelled a route from the eastern tropical North Atlantic to the Adriatic Sea between October 2019 and July 2020 (see Table A6). This 9-month experiment in a transition zone between the temperate and tropical belts represents a major challenge for the SD's operations. The sensors on board were exposed to varying degrees of degradation and biofouling depending on the geographical area and season, which led to a deterioration in the measurements. As a result, some maintenance measures were required during the mission. We address the difficulty of correcting the data during a period of COVID-19 restrictions, which significantly reduced the number of discrete samples planned for the SD salinity and dissolved oxygen validation. This article details alternative correction methods for salinity and dissolved oxygen. Due to the lack of in situ data, model products have been used to correct the salinity data acquired by the SD instruments, and then the resulting corrected salinity was validated with data from fixed ocean stations, gliders, and Argo floats. In addition, dissolved oxygen data acquired from the SD instruments after correction using air oxygen measurements were tested and found to be coherent with the variation in oxygen concentrations expected from changes in temperature and phytoplankton abundance (from chlorophyll a). The correction methods are relevant and useful in situations where validation capabilities are lacking, which was the case during the ATL2MED demonstration experiment. For future experiments, a more frequent sample collection would improve the data qualification and validation.CO2 and hydrography acquired by autonomous surface vehicles from the Atlantic Ocean to the Mediterranean Sea: data correction and validationpublishedVersio